Definition 2.3 (Zero-concentrated differential privacy (zCDP) [1]}) 

Let \(\mathcal {M}: \mathcal {X}^n \rightarrow \Omega \)  be a randomized algorithm where
\(\left( \Omega , \Sigma , \operatornamewithlimits{\mathbb {P}}\right)\)  is a probability space and \(\rho \geqslant 0\) .
We say that \(\mathcal {M}\)  respects \(\rho \) -zCDP if
\( \forall (D, D^{\prime }) \in \mathcal {D}_n, \forall \alpha \in (1, \infty ):H_{\alpha } \left( \mathcal {M}(D) \Vert \mathcal {M}(D^{\prime }) \right) \leqslant \rho \alpha .\) 

